Patents by Inventor Mahadev Khapali
Mahadev Khapali has filed for patents to protect the following inventions. This listing includes patent applications that are pending as well as patents that have already been granted by the United States Patent and Trademark Office (USPTO).
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Patent number: 11481598Abstract: A computer-implemented method for creating an auto-scaled predictive analytics model includes determining, via a processor, whether a queue size of a service master queue is greater than zero. Responsive to determining that the queue size is greater than zero, the processor fetches a count of requests in a plurality of requests in the service master queue and a type for each of the requests. The processor derives a value for time required for each of the requests and retrieves a number of available processing nodes based on the time required for each of the requests. The processor then auto-scales a processing node number responsive to determining that a total execution time for all of the requests in the plurality of requests exceeds a predetermined time value and outputs an auto-scaled predictive analytics model based on the processing node number and queue size.Type: GrantFiled: November 27, 2017Date of Patent: October 25, 2022Assignee: International Business Machines CorporationInventors: Mahadev Khapali, Shashank V. Vagarali
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Patent number: 11481620Abstract: In an approach to deriving highly accurate models, one or more computer processors train a set of machine learning models utilizing a training set and a deep learning algorithm; generate one or more feedback data sets for each model in the set of trained models; rank each model in the set of trained models based on the generated feedback data sets; dynamically adjust one or more thresholds, that initiate a retraining or deployment of one or more ranked models, based, at least in part, on one or more production environment requirements; responsive to exceeding one or more adjusted thresholds, automatically deploy one or more ranked models to one or more deployment environments based, at least in part, on the ranking of the one or more trained models; responsive to not exceeding one or more adjusted thresholds, retrain each model in the set of trained models.Type: GrantFiled: July 29, 2019Date of Patent: October 25, 2022Assignee: International Business Machines CorporationInventors: Mahadev Khapali, Shashank Vijaykumar Vagarali, Yugandhra Rayanki, Prabhu S. Padashetty
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Publication number: 20220292373Abstract: A method for receiving an end-user model access data set, deriving a plurality of patterns of actions typically performed by the end-user based on analysis of the end-user model access data set, and deriving a first model deployment protocol to automatically deploy selected ML models of the plurality of ML models for the end-user when the end-user works with ML models based on the plurality of patterns of actions.Type: ApplicationFiled: March 15, 2021Publication date: September 15, 2022Inventors: Mahadev Khapali, Shashank Vijaykumar Vagarali, Hemant Singh, Yugandhra Rayanki
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Publication number: 20210034960Abstract: In an approach to deriving highly accurate models, one or more computer processors train a set of machine learning models utilizing a training set and a deep learning algorithm; generate one or more feedback data sets for each model in the set of trained models; rank each model in the set of trained models based on the generated feedback data sets; dynamically adjust one or more thresholds, that initiate a retraining or deployment of one or more ranked models, based, at least in part, on one or more production environment requirements; responsive to exceeding one or more adjusted thresholds, automatically deploy one or more ranked models to one or more deployment environments based, at least in part, on the ranking of the one or more trained models; responsive to not exceeding one or more adjusted thresholds, retrain each model in the set of trained models.Type: ApplicationFiled: July 29, 2019Publication date: February 4, 2021Inventors: Mahadev Khapali, Shashank Vijaykumar Vagarali, Yugandhra Rayanki, Prabhu S. Padashetty
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Patent number: 10459916Abstract: A method for updating a plurality of database statistics during a query execution is provided. The method may include receiving a compiled query. The method may also include determining if the received compiled query requires at least one table scan operation on a full table to resolve the received compiled query. The method may further include determining if a plurality of table statistics associated with the full table has not been updated within a pre-defined time-period, whereby the determining is based on the determination that the received compiled query requires at least one table scan operation on the full table to resolve the received compiled query. The method may additionally include collecting a plurality of statistics associated with the full table based on the determination that the plurality of table statistics associated with the full table has not been updated within the pre-defined time-period.Type: GrantFiled: July 31, 2015Date of Patent: October 29, 2019Assignee: International Business Machines CorporationInventors: Samar T. Desai, Dattatreya Govindappanavar, Mahadev Khapali, Mohan Narayanswamy
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Patent number: 10348892Abstract: A computer-implemented method includes identifying a mobile phone. The method includes identifying one or more input devices. The one or more input devices are associated with the mobile phone. The method includes collecting behavior information from the input devices. The method includes applying machine learning to the behavior information to yield a schedule.Type: GrantFiled: June 15, 2016Date of Patent: July 9, 2019Assignee: International Business Machines CorporationInventors: Charan Acharya Chandrashekar, Santosh Hegde, Mahadev Khapali, Shashank V. Vagarali
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Publication number: 20190164033Abstract: A computer-implemented method for creating an auto-scaled predictive analytics model includes determining, via a processor, whether a queue size of a service master queue is greater than zero. Responsive to determining that the queue size is greater than zero, the processor fetches a count of requests in a plurality of requests in the service master queue, and a type for each of the requests. The processor derives a value for time required for each of the requests, and retrieves a number of available processing nodes based on the time required for each of the requests. The processor then auto-scales a processing node number responsive to determining that a total execution time for all of the requests in the plurality of requests exceeds a predetermined time value, and outputs an auto-scaled predictive analytics model based on the processing node number and queue size.Type: ApplicationFiled: November 27, 2017Publication date: May 30, 2019Inventors: Mahadev Khapali, Shashank V. Vagarali
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Patent number: 10007578Abstract: An approach for improving application performance after database recovery is provided, the approach involving tracking one or more applications connecting to a database, tracking metadata in memory on a server computer, wherein the metadata is accessed by the one or more applications, recovering the metadata during a database recovery occurring after a database crash and repopulating the metadata in memory on the server computer during the database recovery, wherein the repopulating occurs prior to the metadata being requested by the one or more applications.Type: GrantFiled: January 12, 2016Date of Patent: June 26, 2018Assignee: International Business Machines CorporationInventors: Santosh Hegde, Mahadev Khapali, Mohan Narayanswamy
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Publication number: 20170366665Abstract: A computer-implemented method includes identifying a mobile phone. The method includes identifying one or more input devices. The one or more input devices are associated with the mobile phone. The method includes collecting behavior information from the input devices. The method includes applying machine learning to the behavior information to yield a schedule.Type: ApplicationFiled: June 15, 2016Publication date: December 21, 2017Inventors: Charan Acharya Chandrashekar, Santosh Hegde, Mahadev Khapali, Shashank V. Vagarali
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Patent number: 9740579Abstract: An approach for improving application performance after database recovery is provided, the approach involving tracking one or more applications connecting to a database, tracking metadata in memory on a server computer, wherein the metadata is accessed by the one or more applications, recovering the metadata during a database recovery occurring after a database crash and repopulating the metadata in memory on the server computer during the database recovery, wherein the repopulating occurs prior to the metadata being requested by the one or more applications.Type: GrantFiled: April 5, 2016Date of Patent: August 22, 2017Assignee: International Business Machines CorporationInventors: Santosh Hegde, Mahadev Khapali, Mohan Narayanswamy
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Publication number: 20170199792Abstract: An approach for improving application performance after database recovery is provided, the approach involving tracking one or more applications connecting to a database, tracking metadata in memory on a server computer, wherein the metadata is accessed by the one or more applications, recovering the metadata during a database recovery occurring after a database crash and repopulating the metadata in memory on the server computer during the database recovery, wherein the repopulating occurs prior to the metadata being requested by the one or more applications.Type: ApplicationFiled: April 5, 2016Publication date: July 13, 2017Inventors: Santosh Hegde, Mahadev Khapali, Mohan Narayanswamy
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Publication number: 20170199790Abstract: An approach for improving application performance after database recovery is provided, the approach involving tracking one or more applications connecting to a database, tracking metadata in memory on a server computer, wherein the metadata is accessed by the one or more applications, recovering the metadata during a database recovery occurring after a database crash and repopulating the metadata in memory on the server computer during the database recovery, wherein the repopulating occurs prior to the metadata being requested by the one or more applications.Type: ApplicationFiled: January 12, 2016Publication date: July 13, 2017Inventors: Santosh Hegde, Mahadev Khapali, Mohan Narayanswamy
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Publication number: 20170031987Abstract: A method for updating a plurality of database statistics during a query execution is provided. The method may include receiving a compiled query. The method may also include determining if the received compiled query requires at least one table scan operation on a full table to resolve the received compiled query. The method may further include determining if a plurality of table statistics associated with the full table has not been updated within a pre-defined time-period, whereby the determining is based on the determination that the received compiled query requires at least one table scan operation on the full table to resolve the received compiled query. The method may additionally include collecting a plurality of statistics associated with the full table based on the determination that the plurality of table statistics associated with the full table has not been updated within the pre-defined time-period.Type: ApplicationFiled: July 31, 2015Publication date: February 2, 2017Inventors: Samar T. Desai, Dattatreya Govindappanavar, Mahadev Khapali, Mohan Narayanswamy